Converging Web-Data and Database Data: Big - and Small Data via Linked Data

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1 DBKDA/WEB Panel 2014, Chamonix, DBKDA/WEB Panel 2014, Chamonix, Reutlingen University Converging Web-Data and Database Data: Big - and Small Data via Linked Data Moderation: Fritz Laux, Reutlingen University, Germany F. Laux Panelists: Andreas Schmidt, Karlsruhe Univ. of Applied Sciences and Karlsruhe Institute of Technology (KIT), Germany Iztok Savnik, University of Primorska, Slovenia Kiyoshi Nitta, Yahoo Japan Research, Japan Hermann Kaindl, Vienna Univ. of Technology, Austria Characterization of Web- and DB-Data Reutlingen University Web-Data Semi-structured: ad-hoc structure, verbose self-describing format parsing (inefficient storing and retrieval) Size: largest data collection unable to fit in central DBMS Quality: inconsistent, redundant unreliable quality (approximate) Search is by keywords DB-Data structured: well defined formal data model efficient storing and retrieval Size: limited to a specific domain Quality: consistent, reliable (exact) Query by logical expression What should converge? 2 /5 F. Laux 1

2 DBKDA/WEB Panel 2014, Chamonix, Characterization of Big and Small Data Reutlingen University Big Data Data that cannot be handled by a single system Considering storage and processing power Mostly generated by machines or sensors - structured data, not text data industry 4.0 Origin is unclear John R. Mashey (sgi): Big Data... Presentation on the next technology wave in 1998 Data rich, but information poor Small Data It is not the complement of Big Data! Small data connects people with timely, meaningful insights, organized and packaged to be accessible, understandable, and actionable for everyday tasks (URL: 2013) Highly condensed and usable information/knowledge 3 /5 F. Laux What should converge? Criteria for convergence Reutlingen University What should converge? Necessary conditions from the user s perspective Semantics User friendliness, quality Quality (performance, reliability, correctness) Necessary conditions from the developer s perspective Common data model, knowledge presentation Structure agnostic query/search Efficient query and reliable transaction technology 4 /5 F. Laux We need the convergence for all of the above! 2

3 DBKDA/WEB Panel 2014, Chamonix, Semantics: Model convergence Reutlingen University Tension field between schema strictness and structural complexity Formal strictness Rel. oom XML Schema RDF Tree DAG Graph 5 /5 F. Laux To converge Web- and DB Data we need semantics and ultimately distill valuable knowledge out of the data! Structural complexity 3

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7 DBKDA-2014 Panel The Sixth International Conference on Advances in Databases, Knowledge, and Data Applications April 20-26, Chamonix, France Advances on Converging WEB Data and Database Data: Big Data and Small Data via Linked Data Andreas Schmidt (1) Department of Informatics and Business Information Systems University of Applied Sciences Karlsruhe Moltkestraße Karlsruhe Germany (2) Institute for Applied Sciences Karlsruhe Institute of Technologie PO-box Karlsruhe Germany Andreas Schmidt - DBKDA/WEB Panel /9

8 Terminology What is... Big Data? Small Data? Linked Data? Andreas Schmidt - DBKDA/WEB Panel /9

9 Terminology What is... Big Data... a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. [Snijders, C., Matzat, U., & Reips, U.-D. (2012). Big Data : Big gaps of knowledge in the field of Internet. International Journal of Internet Science, 7, 1-5] Big data is difficult to work with using most relational database management systems and desktop statistics and visualization packages, requiring instead "massively parallel software running on tens, hundreds, or even thousands of servers" [Jacobs, A. (6 July 2009). "The Pathologies of Big Data". ACMQueue] Small Data Linked Data Andreas Schmidt - DBKDA/WEB Panel /9

10 Terminology What is... Big Data Small Data Small data is the amount of data you can conveniently store and process on a single machine, and in particular, a high-end laptop or server (Rufus Pollok, Open Knowledge Foundation) Small data connects people with timely, meaningful insights (derived from big data and/or local sources), organized and packaged often visually to be accessible, understandable, and actionable for everyday tasks (Alan Bonde)] Linked Data Andreas Schmidt - DBKDA/WEB Panel /9

11 Terminology What is... Big Data Small Data Linked Data... describes a method of publishing structured data so that it can be interlinked and become more useful [http://en.wikipedia.org/wiki/linked_data] It builds upon standard Web technologies such as HTTP, RDF and URIs [] Origin: Open (Government) Data Andreas Schmidt - DBKDA/WEB Panel /9

12 Terminology Converging f(x) = 2x^3-7x^ g(x) = (12x^5-14x + 3)/(4x^2 + 2x) lim (f(x) / g(x)) = 2/3 x->oo Andreas Schmidt - DBKDA/WEB Panel /9

13 Converging WEB Data and Database Data lim ( web data t / database data t ) = epsilon t->future how does op(...) looks like? or, a little be more formal... lim ( op(web data t ) / op(database data t ) ) = epsilon t->future what is epsilon? Andreas Schmidt - DBKDA/WEB Panel /9

14 Big Data and Small Data via Linked Data linkify(big Data) => linked data linkify(small Data) => linked data Database Data => Web Data Andreas Schmidt - DBKDA/WEB Panel /9

15 Bizer, Christian; Heath, Tom; Berners-Lee, Tim (2009). "Linked Data The Story So Far". International Journal on Semantic Web and Information Systems 5 (3): 122 Jacobs, A. (6 July 2009). "The Pathologies of Big Data". ACMQueue Snijders, C., Matzat, U., & Reips, U.-D. (2012). Big Data : Big gaps of knowledge in the field of Internet. International Journal of Internet Science, 7, 1-5 Andreas Schmidt - DBKDA/WEB Panel /9

16 Data and Knowledge: One Man s Opinion Institut für Computertechnik Hermann Kaindl Vienna University of Technology, Austria ICT Institute of Computer Technology

17 Value Chain Knowledge Management Institute of Computer Technology 2

18 Datentechnik (data technology) From WWW to Semantic Web Miscellenious From GPS-driven navigation tools to Google cars Data in the Cloud Data looked outdated for a while, when everything seemed to be knowledge, but now data seem to be ubiquitous! Institute of Computer Technology

19 Thank you for your attention! Institute of Computer Technology 4

20 Current state of graph databases Iztok Savnik University of Primorska & Jožef Stefan Institute Panel: Big Data and Small Data via Linked Data DBKDA, 2014

21 Terminology Linked data Linked Open Data Open data Graph databases Knowledge bases Knowledge graphs

22 Wordnet Princeton's large lexical database of English. Cognitve synonims: synsets concepts Synsets are linked by: 117,000 synsets conceptual-semantic relationships, and lexical relationships. Include definitions of synsets. Main relationships: Synonymy, hyponymy (ISA), meronymy (part-whole), antonymy

23 Linked Open Data Datasets are represented in RDF Wikipedia, Wikibooks, Geonames, MusicBrainz, WordNet, DBLP bibliography Number of triples: 33 Giga (10 9) (2011) Governments: USA, UK, Japan, Austria, Belgium, France, Germany,... Active community

24 Freebase Free, knowledge graph: people, places and things, 2,478,168,612 facts, 43,459,442 topics Semantic search engines are here!

25 Freebase Based on graphs: nodes, links, types, properties, namespaces Google use of Freebase Knowledge graph Words become concepts Semantic questions Semantic associations Browsing knowledge Knowledge engine Available in RDF

26 YAGO 10 Mega (106) concepts Max Planc Institute, Informatik Accuracy of 95% Includes: Wikipedia, WordNet, GeoNames Links Wordnet to Wikipedia taxonomy (350K concepts) Anchored in time and space

27 Wikidata Free knowledge base with 14,550,852 items Collecting structured data Properties of person, organization, works, events, etc.

28 Wikidata Free knowledge base with 14,550,852 items

29 Cyc - knowledge base Knowledge base Doug Lenat Conceptual networks (ontologies) Higher ontology, basic theories, specific theories Predefined semantic relationships Common sense reasoner Based on predicate calculus Rule-based reasoning 10

30 Cyc 11

31 Some conclusions There exist a variety of different dictionaries, properties, concepts,... There exist a variety of formats and models for knowledge and data representation Common definitions are not frequent RDF is common data/knowledge model Senses of words are not represented

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